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Salt rock from salt lakes can serve as a cost-effective material for subgrade filling, as demonstrated in projects like the Qarhan Salt Lake section of the Qinghai-Tibet Railway and the Qarhan Salt Lake section of the G215 Highway. This state-of-the-art paper aims to summarize the engineering properties of salt rock filling and present the advances of its utilization.

This paper collects and analyzes laboratory and field data of salt rock filling from previous studies to present a comprehensive analysis of the engineering properties and utilization of salt rock fillings.

Salt rock primarily contains minerals such as halite and glauberite, which contribute to its unique phase-changing behavior under varying environmental conditions, impacting its mechanical properties. Salt rock filling shrinks when in contact with vapor or unsaturated brine and expands under cooling or evaporation. Its use is particularly recommended for arid regions, with specific restrictions depending on the structure type. This paper discusses suggested countermeasures to mitigate these issues, as well as key quality acceptance indices for salt rock filling compaction. Moisture content after air-drying is recommended as a crucial parameter for construction quality control.

This review aims to support future research and engineering practices in salt rock subgrade applications.

Drawing on the technology affordance and affinity theories, this study proposes a framework explaining the antecedents and consequences of customers’ smart experiences (CSEs) in the artificial intelligence (AI) chatbot context.

The quantitative approach employing an online survey was adopted to obtain data from chatbot users (N = 761) and analyzed using structural equation modeling.

Results from a survey study show that chatbot affordances, including interactivity (two-way communication, active control and synchronicity), selectivity (customization and localization), information (argument quality and source credibility), association (connectivity and sense of safety) and navigation positively affect CSEs (hedonic and cognitive), leading to customer chatbot stickiness through affinity.

Our study provides evidence that supports and extends the affordances and affinity lens by highlighting the roles of specific chatbot affordances that contribute to a positive-smart experience and subsequently enhances customer chatbot stickiness through affinity.

This study aims to streamline and enhance the assembly defect inspection process in diesel engine production. Traditional manual inspection methods are labor-intensive and time-consuming because of the complex structures of the engines and the noisy workshop environment. This study’s robotic system aims to alleviate these challenges by automating the inspection process and enabling easy remote inspection, thereby freeing workers from heavy fieldwork.

This study’s system uses a robotic arm to traverse and capture images of key components of the engine. This study uses anomaly detection algorithms to automatically identify defects in the captured images. Additionally, this system is enhanced by digital twin technology, which provides inspectors with various tools to designate components of interest in the engine and assist in defect checking and annotation. This integration facilitates smooth transitions from manual to automatic inspection within a short period.

Through evaluations and user studies conducted over a relatively long period, the authors found that the system accelerates and improves the accuracy of engine inspections. The results indicate that the system significantly enhances the efficiency of production processes for manufacturers.

The system represents a novel approach to engine inspection, leveraging robotic technology and digital twin enhancements to address the limitations of traditional manual inspection methods. By automating and enhancing the inspection process, the system offers manufacturers the opportunity to improve production efficiency and ensure the quality of diesel engines.

Although there is growing critical awareness in ELT around the rise of English as a global language, studies on teachers’ investment in critical pedagogy remain limited in mainstream ELT curricula, and the impact of such investment on teachers’ identities is not clear. To address this gap, with the inclusive paradigm of Global Englishes (GE), the paper presents a case study of an English teacher’s investment in GE at a middle school in China.

This study employed a qualitative approach. Semi-structured interview was conducted with the participant – May, focusing on her reported practices and her understanding of her roles during the investment in GE. The interview process was guided by an interview protocol which was designed based on related literature on GE, the theoretical framework, and the research context. A content analysis method was utilized to generate descriptive categories concerning participant’s identities and investment in GE.

Analysis of interview data reveals that through investment in GE, May not only constructed her identity as an English teacher, but also explored identities as a student inspirer, and a peer mentor. These identities exploration and construction were primarily driven by her increased cultural and social capital, despite facing challenges such as high-stakes test policies, native-speakerism ideology, institutional requirements, and limited resources.

Future research incorporating triangulating data such as interviews, and classroom observations, would provide a more comprehensive understanding of English teachers’ identities, and investment in GE. Besides, the findings of this study are primarily from one teacher, they may not fully represent the broader population of English teachers in China.

The findings have several implications for English teaching and teacher education. First, elementary schools, the lower grades of middle schools (grades 7 and 8), or the after-school programs may have opportunities for teachers to integrate GE in teaching. Second, teacher education programs should be designed to provide more chances that enable student teachers to invest in their learning and teaching of GE. Third, proposals for incorporating GE practices in the classroom must adopt a critical perspective, so as to to expose, deconstruct, and reconstruct power dynamics that influence teachers’ investment in GE.

The originality of this study lies in its exploration of English teachers’ investment of GE in their teaching, and the impact of this investment on their identities as English teachers. By investigating these aspects, the study addresses the research gaps in English teachers’ practice of integration of GE in mainstream ELT curricula and provides insights on how to encourage English teachers to incorporate a GE-aware perspective in their teaching.

Recently tourist destinations are facing serious issues of environmental degradation and destination managers are developing strategies to achieve the sustainable destinations’ natural environment. The primary purpose of this study is to analyze the role of green destination brand equity (DBE) in shaping tourists’ environmentally responsible behavior (ERB). Green DBE is analyzed through green destination awareness (GDA), green destination image (GDI), green destination quality (GDQ) and green destination loyalty (GDL). Furthermore, perceived destination trust (PDT) is considered a mediator, and green perceived value is a moderator to explain the tourists’ ERB.

Respondents attending the green-certified destinations were approached physically, and data was gathered from 701 respondents through a self-administered survey method.

Results of the study indicated a significant effect of GDA on GDI and GDQ while an insignificant effect on GDL. Study found significant effect of GDI on GDQ and GDL. Study indicated significant effect of GDQ on GDL. Results of the study indicated significant effect of GDA, GDI, GDQ and GDL on tourists’ ERB. Furthermore, PDT significantly mediated the relationship between green DBE and tourists’ ERB. Finally, moderation results for green destination value (GPV) were significant between green DBE and tourists’ ERB.

Based on the theoretical perspectives of the simulation-organism-response model, a study has explained the influence of green DBE destinations on tourists’ ERB. The study has significantly used the concept of green DBE to explain tourists’ ERB and endorsed the importance of branding in achieving a sustainable tourist destination environment. Finally, the study has uniquely explained tourists’ ERB with the PDT and GPV. The study has highlighted the significance of green branding strategies in protecting the destination environment through shaping tourists’ ERB.

This study presents a systematic literature review (SLR) of the interdisciplinary literature on drones in last-mile delivery (LMD) to extrapolate pertinent insights from and into the logistics management field.

Rooting their analytical categories in the LMD literature, the authors performed a deductive, theory refinement SLR on 307 interdisciplinary journal articles published during 2015–2022 to integrate this emergent phenomenon into the field.

The authors derived the potentials, challenges and solutions of drone deliveries in relation to 12 LMD criteria dispersed across four stakeholder groups: senders, receivers, regulators and societies. Relationships between these criteria were also identified.

This review contributes to logistics management by offering a current, nuanced and multifaceted discussion of drones' potential to improve the LMD process together with the challenges and solutions involved.

The authors provide logistics managers with a holistic roadmap to help them make informed decisions about adopting drones in their delivery systems. Regulators and society members also gain insights into the prospects, requirements and repercussions of drone deliveries.

This is one of the first SLRs on drone applications in LMD from a logistics management perspective.

This paper aims to explore the underlying mechanisms and boundary conditions through which equipment manufacturing enterprises can capture market value from digital transformation, with a specific focus on the roles of knowledge search and knowledge recombination.

This study uses a double fixed-effects model to test the hypotheses, using a unique data set of “firm-year” observations from 739 publicly listed equipment manufacturing companies in China, spanning the period from 2018 to 2022.

Digital transformation drives market value creation in equipment manufacturing enterprises through both breakthrough knowledge recombination (BKR) and progressive knowledge recombination (PKR). In addition, the analysis of marginal conditions reveals that diversified knowledge search serves as a substitute for digital transformation in promoting BKR, while also positively moderating the relationship between digital transformation and PKR.

Grounded in the knowledge-based view theoretical framework, this study introduces the novel concepts of BKR and PKR and systematically examines how digital transformation impacts market value in equipment manufacturing enterprises.

In view of the unknown environmental parameters and uncertain interference during gripping by the manipulator, it is difficult to obtain an effective gripping force with the traditional impedance control method. To avoid this dilemma, the purpose of this study is to propose an adaptive control strategy based on an adaptive neural network and a PID search optimization algorithm for unknown environments.

The method is based on a variable impedance model, and a new impedance model is established using a radial basis function (RBF) neural network to estimate unknown parameters of the impedance model. The approximation errors of the adaptive neural network and the uncertain disturbance are effectively suppressed by designing the adaptive rate. In the meantime, auxiliary variables are constructed for Lyapunov stability analysis and adaptive controller design, and PSA is used to ensure the stability of the adaptive impedance control system. Based on the Lyapunov stability criterion, the adaptive im-pedance control system is proved to have progressive tracking convergence property.

Through comparative simulations and experiments, the superiority of the proposed adaptive control strategy in position and force tracking has been verified. For objects with low flexibility and light-weight (such as a coke, a banana and a nectarine), this control method demonstrates errors of less than 10%.

This paper uses RBF neural networks to estimate unknown parameters of the impedance model in real-time, enhancing system adaptability. Neural network weights are updated online to suppress errors and disturbances. Auxiliary variables are designed for Lyapunov stability analysis. The PSA algorithm is used to adjust controller parameters in real-time. Additionally, comparative simulations and experi-ments are designed to analyze and validate the performance of controller.

The purpose of the study is to test the precursors of presenteeism. The research has examined the relationship between workplace bullying and presenteeism via depression and anxiety. Furthermore, moderating the role of toxic leadership is also investigated which may strengthen or weaken workplace bullying and mental health relationships.

The mediations and moderation models were tested in SPSS software through the Preacher and Hayes PROCESS macro technique. Data was gathered from 165 employees, working in public and private universities of Pakistan.

The results supported that depression and anxiety act as mediators in the relationship between bullying and presenteeism. Further, toxic leadership moderated the relationship between bullying and depression, bullying and anxiety.

As per the author’s knowledge, rare studies have determined that bullying can increase mental health issues and presenteeism in employees. Bullying and toxic leadership together increase the loss of psychological resources that force employees to work while feeling sick.

This study aims to provide a comprehensive analysis of two-sided matching (TSM) research, an interdisciplinary field that integrates both theoretical and practical perspectives. By examining 756 research articles from the Web of Science database, this paper seeks to identify key trends, collaboration patterns and emerging research topics within the TSM domain.

The research utilizes bibliometric analysis combined with a structural topic model to analyze TSM-related articles published between January 1, 2000, and September 30, 2022. The study identifies leading subfields, journals, countries/regions and institutions based on publication volume, total citations and average citations per article. Interaction and collaboration patterns among these entities are examined through co-occurrence and coupling networks. Additionally, five major research topics are identified and explored using topic modeling and co-word networks. This hybrid knowledge mining approach better reveals the inherent structural changes in topic clusters. Topic distribution and network analysis are beneficial in capturing the attention allocation of different entities to knowledge.

The analysis reveals five prominent research topics in TSM: communication resource allocation, stable matching research, computing task assignment, TSM decision-making and market matching mechanism design. These topics represent the main directions of TSM research. The study also uncovers a shift in research focus from theoretical aspects to practical applications. Furthermore, the distribution of knowledge and interaction patterns among key entities align with the identified research trends.

This study offers a novel and detailed overview of TSM research highlighting significant trends and collaboration patterns within the field. By integrating bibliometric methods with structural topic modeling the study provides unique insights into the evolution of TSM research making it a valuable resource for both academic and professional communities.